1. Field of Invention
The present invention relates to a crest factor reduction technique in a communication field, and particularly to a method and an apparatus for peak cancellation crest factor reduction in a Radio Remote Unit (RRU) in a wireless communication system.
2. Description of Prior Art
Peak-to-average power ratio (PAPR) is one of the most critical problems of Orthogonal Frequency Division Modulation (OFDM). Generated by summation of a large number of subcarriers, an OFDM signal usually has a high PAPR. In a radio front end, high PAPR may lead to serious back-off of power amplifiers (PAs), and result in a low efficiency of the PA.
To reduce the PAPR of OFDM, a series of Crest Factor Reduction (CFR) techniques have been introduced in reference document [1] (W. B. Wang, K. Zheng, “Wideband wireless communication OFDM technology”, pp. 93-110, China Posts and Telecom Press, 2007). In baseband processing, most PAPR reduction methods are based on redundancy employing such as coding, selective mapping and tone reservation. These techniques cause no signal distortion, but severe computation complexity and lower spectrum efficiency. Furthermore, for multicarrier application, baseband processing schemes can hardly predict the PAPR after interpolation and carrier combination. Therefore, it is better to reduce PAPR in a digital Intermediate Frequency (IF) domain after carrier combination. And the most efficient way to reduce PAPR in the digital IF is clipping.
Clipping is a non-linear process that may cause severe in-band distortion and out-band noise. In-band distortion leads to Error Vector Magnitude (EVM), Signal-to-Noise Ratio (SNR) and Block Error Rate (BLER) degradation, while out-band noise may cause Adjacent Channel Leakage Ratio (ACLR) failure. Therefore, it is important to design the clipping algorithm deliberately to reduce PAPR with limited EVM and ACLR degradation.
Noise Shaping Crest Factor Reduction (NS-CFR) and Peak Cancellation Crest Factor Reduction (PC-CFR) are two of the most popular clipping algorithms. As shown in FIG. 1 (a), a NS-CFR algorithm 100a may extract an input signal above of a predetermined clipping threshold in a peak extraction block 110a, and reshape it by a filtering block 130a. Then the input signal delayed by a matched delay block 150a may be subtracted by this shaped peak signal.
A PC-CFR algorithm may generate a pre-shaped peak signal when a peak is detected. Then this pre-shaped peak may be scaled and subtracted from the input signal. As seen from FIG. 1(b), which shows a typical structure of the PC-CFR algorithm 100b, when a peak is detected by the peak detection block 110b, the PC-CFR algorithm 100b allocates the peak to one of the cancellation units inside the peak cancellation block 130b, so as to generate the pre-shaped and scaled cancellation peak to be subtracted from the input signal delayed by the match delay block 150b. 
Generally, peaks of a Long-Term Evolution (LTE) signal arrive in low probabilities. This indicates a significant characteristic of signal peaks—sparsity. The PC-CFR algorithm may exploit the sparsity of signal peaks. A small number of peak cancellation units may be enough to do the clipping task, therefore hardware resource may be greatly reduced. As for clipping performance, in general, the NS-CFR algorithm has a comparable performance with the PC-CFR algorithm, because the intrinsic principles of these algorithms are similar. But specifically, the PC-CFR algorithm works a little better than the NS-CFR algorithm in metric of PAPR and EVM, as shown in reference document [2] (E. Hemphill, S. Summerfield, G. Wang, and D. Hawke, “Peak Cancellation Crest Factor Reduction Reference Design”, XAPP1033 (V1.0), Xilinx, Nov. 18, 2007). In reference document [3] (W. B. Wang, K. Zheng, “Wideband wireless communication OFDM technology”, pp. 93, China Posts and Telecom Press, 2007), simulations also show that the PC-CFR algorithm is better measured by PAPR reduction and SNR drop.
Hereinafter, a detailed block diagram of a PC-CFR unit using the PC-CFR algorithm in the prior art may be described with reference to FIG. 2.
FIG. 2 illustratively shows a detailed block diagram of a PC-CFR unit 200. As shown in FIG. 2, the PC-CFR unit 200 may comprise a peak detector 210 including a peak extractor 211 and a peak indication unit 213, an allocator 220, a plurality of peak cancellation units 230s (here are four peak cancellation units 230s as an example), a summation unit 240, a matched delay unit 250, and a subtraction unit 260.
The peak detector 210 may detect a peak from an input signal. Generally, the detection of the peak may be carried out on magnitude of the input signal.
In particular, the peak extractor 211 may calculate the magnitude and a phase of the input signal using e.g. Coordinate Rotational Digital Computer (CORDIC) algorithm. Then, the peak extractor 211 may subtract the magnitude of the input signal by a predetermined clipping threshold to obtain a magnitude difference DMag between the magnitude and the threshold. The threshold may be determined based on PARP requirement and an average power of the input signal.
The peak indication unit 213 may indicate a maximum value of the DMags as a peak indicator for a peak. The maximum value may be obtained by comparison with neighboring values. It can either be a local max value or a global max value in a given time window, as will be understood by the skilled in the art.
Once an incoming peak is detected, the allocator 220 may allocate the peak to one of the peak cancellation units 230s for generating a cancellation peak. As well-known by the skilled in the art, the “peak” here is actually represented by peak information on the detected peak of the input signal, which includes the magnitude difference DMag and the phase of the detected peak. The term “peak” is used here and hereinafter for simplicity.
In this example, it is assumed that there are four peak cancellation units 230s. Each peak cancellation unit 230 may cancel only one peak at a time. The length of the cancellation peak together with the number of the peak cancellation units 230s may determine a rate at which the peaks may be cancelled. When a new peak is detected, the allocator 220 may assign an available peak cancellation unit 230 to cancel that peak. If all the peak cancellation units 230s are unavailable when a new peak is detected, the peak will not be cancelled. Multiple iterations of PC-CFR may be necessary to eliminate the peaks that were not cancelled during an earlier PC-CFR process.
The magnitude of the cancellation peak may be scaled to the magnitude difference DMag between the corresponding peak magnitude and the clipping threshold. The cancellation peak may be designed to have a spectrum that matches that of the input signal and therefore may only introduce negligible out-of-band interference. The cancellation peak may be stored as cancellation peak coefficients in a RAM in advance. Generally, the peak cancellation unit 230 may include two blocks of RAM for storing the input signal (one for storing I coefficients and one for storing Q coefficients) and one complex multiplier which may include four DSP multipliers for scaling. As will be understood by the skilled in the art, the cancellation peak coefficients may be predetermined by carrier configuration including carrier number, carrier frequency and carrier bandwidth etc. For example, in the application of a single carrier with a central frequency of 0, the spectrum shape is rectangular, which corresponds to a set of coefficients like a sinc waveform in the time domain.
Once the incoming peak is allocated to one of the peak cancellation units 230s, these coefficients will be read out sequentially. Then the cancellation peak coefficients may be scaled by the magnitude difference DMag and the phase of the incoming peak in the peak cancellation unit 230. Although there are four peak cancellation units 230s in this example, the number of the peak cancellation units may be varied depending on actual design demands in consideration of e.g. the carrier number, the carrier bandwidth, and statistic characteristics of the carrier data.
Then, outputs of all the cancellation units 230s may be summed in the summation unit 240. And the sum from the summation unit 240 may be subtracted from a delayed input signal output from the matched delay unit 250 by the subtraction unit 260.
Since the number of peak cancellation units is limited, it is always possible that when all peak cancellation units are occupied, it is unable to process new coming peaks. This will lead to peak leakage and bring a high risk to the PA. In order to mitigate the peak leakage problem and achieve better performance, iterative clipping may be used. For a single carrier LTE application with a bandwidth of 20 MHz, a simulation and on-board test shows that the PC-CFR with 2˜4 stages of clipping is suitable.
Unfortunately, for various reasons, the current PC CFR algorithm may not be efficient any more for a multicarrier LTE application with carrier number no less than 2 and a signal bandwidth no less than 40 MHz.
Firstly, the PAPR of the input signal grows along with the increase of carrier number, since for the OFDM signal, PAPR≈N, N is the total sub-carrier number (reference document [4] X. Li, L. J. Cimini Jr, “Effects of Clipping and Filtering on the Performance of OFDM” in Proc. of Vehicular Technology Conference, IEEE, pp. 1634, 1997 Invention Information). FIG. 3 shows an example that the PAPR grows along with carrier number. This problem brings a serious challenge to the PC-CFR algorithm, since the arrival rate of peaks grows severely with the increase of PAPR, which may lead to a much larger number of peak cancellation units and clipping stages, also higher risk of peak leakage.
Secondly, the sample rate in the digital IF must be high enough for interpolation and carrier combination. Implementation of digital pre-distortion (DPD) also requires a high oversampling rate. These result in a sample rate higher than 200 MHz in the digital IF. For PC CFR, a higher sample rate will lead to a higher order of coefficients and more difficult for time division multiplexing. Furthermore, peak re-growth after filtering and interpolation will compromise the reduction of PAPR for wideband signal after clipping. These challenges cause poor clipping performance. Iterative clipping may mitigate the degraded performance problem, but results in exponentially increase of clipping stages. Fractional filter between clipping stages may mitigate the effect of peak re-growth, but also needs extra filters for each stage. Therefore, the hardware implementation will be far more complicated and power consumption will be much higher. As an example, according to an on-board test, for a 2×20 MHz LTE application scenario, with 11 dB PAPR at 0.01% probability, the PC CFR algorithm works at a sample rate of 122.88 MHz after carrier combination. If one clipping stage contains four peak cancellation units, it will need 5˜6 stages of clipping at least to get PAPR≦8 dB and EVM≦5% for a transceiver (TRX) board output.
For all these reasons, previous PC-CFR algorithm can hardly work efficiently in the multicarrier LTE application. There is a desire of simplifying design, in order to address at least some of the serious challenges brought by the multicarrier LTE application.